Exploring association between perceived importance of travel/traffic information and travel behaviour in natural disasters : a case study of the 2011 Brisbane floods

A sound understanding of travellers’ behavioural changes and adaptation when facing a natural disaster is a key factor in efficiently and effectively managing transport networks at such times. This study specifically investigates the importance of travel/traffic information and its impact on travel behaviour during natural disasters. Using the 2011 Brisbane flood as a case study, survey respondents’ perceptions of the importance of travel/traffic information before, during, and after the flood were modelled using random-effects ordered logit. A hysteresis phenomenon was observed: respondents’ perceptions of the importance of travel/traffic information increased during the flood, and although its perceived importance decreased after the flood, it did not return to the pre-flood level. Results also reveal that socio-demographic features (such as gender and age) have a significant impact on respondents’ perceptions of the importance of travel/traffic information. The roles of travel time and safety in a respondent’s trip planning are also significantly correlated to their perception of the importance of this information. The analysis further shows that during the flood, respondents generally thought that travel/traffic information was important, and adjusted their travel plans according to information received. When controlling for other factors, the estimated odds of changing routes and cancelling trips for a respondent who thought that travel/traffic information was important, are respectively about three times and seven times the estimated odds for a respondent who thought that travel/traffic information was not important. In contrast, after the flood, the influence of travel/traffic information on respondents’ travel behaviour diminishes. Finally, the analysis shows no evidence of the influence of travel/traffic information’s on respondents’ travel mode; this indicates that inducing travel mode change is a challenging task.

Influence of traffic characteristics on polycyclic aromatic hydrocarbon build-up on urban road surfaces

Traffic is one of the prominent sources of polycyclic aromatic hydrocarbons (PAHs) and road surfaces are the most critical platform for stormwater pollution. Build-up of pollutants on road surfaces was the focus of this research study. The study found that PAHs build-up on road surfaces primarily originate from traffic activities, specifically gasoline powered vehicles. Other sources such as diesel vehicles, industrial oil combustion and incineration were also found to contribute to the PAH build-up. Additionally, the study explored the linkages between concentrations of PAHs and traffic characteristics such as traffic volume, vehicle mix and traffic flow. While traffic congestion was found to be positively correlated with 6- ring and 5- ring PAHs in road build-up, it was negatively correlated with 3-ring and 4 ring PAHs. The absence of positive correlation between 3-ring and 4-ring PAHs and traffic parameters is attributed to the propensity of these relatively volatile PAHs to undergo re-suspension and evaporation. The outcomes of this study are expected to contribute effective transport and land use planning for the prevention of PAH pollution in the urban environment.

Are road traffic crash fatality rates converging among OECD countries?

This article examines the trends of road traffic crash (RTC) fatality rates in OECD countries over the past four decades. Based on recent developments in the economic growth literature we propose and test the hypothesis that RTC fatality rates initially increase with economic development, peak, and then gradually decrease. The theory predicts that, as a result, the RTC fatality rates of different countries will tend to converge over time. Our results for the period 1961–2007 reveal no evidence of the convergence of RTC fatality rates across the OECD as a whole for that time period. Nevertheless, there is evidence of convergence among sub-groups of countries. This evidence may assist policymakers as an additional way of benchmarking their country's performance against that of its peers and to identify the next-closest peer in country sub-groups with superior road safety performance.

Ultrafine Particles from Traffic Emissions and Children’s Health (UPTECH) in Brisbane, Queensland (Australia): Study design and implementation

Ultrafine particles are particles that are less than 0.1 micrometres (µm) in diameter. Due to their very small size they can penetrate deep into the lungs, and potentially cause more damage than larger particles. The Ultrafine Particles from Traffic Emissions and Children’s Health (UPTECH) study is the first Australian epidemiological study to assess the health effects of ultrafine particles on children’s health in general and peripheral airways in particular. The study is being conducted in Brisbane, Australia. Continuous indoor and outdoor air pollution monitoring was conducted within each of the twenty five participating school campuses to measure particulate matter, including in the ultrafine size range, and gases. Respiratory health effects were evaluated by conducting the following tests on participating children at each school: spirometry, forced oscillation technique (FOT) and multiple breath nitrogen washout test (MBNW) (to assess airway function), fraction of exhaled nitric oxide (FeNO, to assess airway inflammation), blood cotinine levels (to assess exposure to second-hand tobacco smoke), and serum C-reactive protein (CRP) levels (to measure systemic inflammation). A pilot study was conducted prior to commencing the main study to assess the feasibility and reliably of measurement of some of the clinical tests that have been proposed for the main study. Air pollutant exposure measurements were not included in the pilot study.

Estimating link-dependent origin-destination matrices from sample trajectories and traffic counts

In transport networks, Origin-Destination matrices (ODM) are classically estimated from road traffic counts whereas recent technologies grant also access to sample car trajectories. One example is the deployment in cities of Bluetooth scanners that measure the trajectories of Bluetooth equipped cars. Exploiting such sample trajectory information, the classical ODM estimation problem is here extended into a link-dependent ODM (LODM) one. This much larger size estimation problem is formulated here in a variational form as an inverse problem. We develop a convex optimization resolution algorithm that incorporates network constraints. We study the result of the proposed algorithm on simulated network traffic.